ABSTRACT The phenomenon consisting in all the feasible region of a multiple objective linear programming problem being weakly efficient, may be less unlikely than has been believed, particularly for problems whose feasible regions have no interior. To deal with such possibility of complete weak efficiency, we would want to have at our disposal proficient methods to check this situation. So, in ...

This paper gives a brief introduction into multiple objective linear programming and discusses its possibilities in the area of forest management. We overview basic concepts, formulations, and principles of solving multiple objective linear programming problems. As such problems s always require the intervention of a decision-maker behavioral aspectsare also considered. We use an application by...

We interpret fuzzy multiple objective linear programming (FMOLP) problems with fuzzy coefficients and fuzzy inequality relations as multiple fuzzy reasoning schemes (MFR), where the antecedents of the scheme correspond to the constraints of the FMOLP problem and the facts of the scheme are the objectives of the FMOLP problem. Then the solution process consists of two steps: first, for every dec...

In this paper, we improve the fuzzy compromise approach of Guu and Wu by automatically computing proper membership thresholds instead of choosing them. Indeed, in practice, choosing membership thresholds arbitrarily may result in an infeasible optimization problem. Although we can adjust minimum satisfaction degree to get fuzzy efficient solution, it sometimes makes the process of interactionmo...

i This paper describes a solution technique mr Linear Programming problems with multiple objective functions. In this type of problem it is often necessary to replace the concept of "optimgm" with that of "best compromise". In contrast with methods dealing with a priori weighted sums of the objective functions, the method described here involves a sequential exploration of solutions. This explo...

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLPs). Job balance, speedup and scalability are of primary interest in evaluating e ciency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm signi cantly speeds up the process of solving MOLPs, which is understood as generating al...